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Not yet recruitingNCT07307547AI-COLOADRUpdated Sep 16, 2026

Effectiveness of Artificial Intelligence-Assisted Colonoscopy for Adenoma Detection in Routine Clinical Practice : a Prospective Multicenter Randomized Trial

An interventional study of AI-Assisted Colonoscopy in Colorectal Neoplasms, Colonic Polyp and Adenoma, sponsored by Zhejiang University. Not yet recruiting at 1 site in China. Open to participants aged 40 Years to 74 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2026-09-16.

Sponsored by Zhejiang University · Not applicable, Interventional, and Screening

Phase
Not applicable
Study type
Interventional
Enrollment
3,300
Allocation
Randomized
Ages
40 Years to 74 Years
Sex
All
01

Study summary

This study is a multi-center, randomized controlled trial designed to evaluate whether an artificial intelligence (AI) system can assist endoscopists to improve the detection rate of colorectal adenomas and cancers during colonoscopy compared to standard colonoscopy. Early screening and diagnosis are key to reducing the burden of colorectal cancer, but current colonoscopy has limitations, including the risk of missed lesions. This trial aims to determine if AI can enhance screening quality and diagnostic accuracy.

Read the detailed description

Colorectal cancer (CRC) screening is crucial for early detection and reducing mortality, yet current colonoscopy techniques face challenges such as variable adenoma detection rates (ADR) and the risk of missed diagnoses for subtle lesions. This study is a prospective, multi-center, parallel-group, randomized controlled trial aiming to validate the clinical value of an AI-assisted diagnostic system in improving screening quality. A total of 3300 participants will be randomized in a 1:1 ratio to undergo either AI-assisted colonoscopy (Experimental Group) or conventional high-definition colonoscopy (Control Group). The primary objective is to compare the ADR between the two groups. Secondary objectives include assessing the detection rate of advanced or specific types of polyps, the mean number of adenomas per procedure, and the impact of the AI system on both patient and physician satisfaction. The study will provide high-quality evidence for the standardized application of AI technology in CRC screening, with the ultimate goal of reducing the incidence and mortality of colorectal cancer.

02

Conditions studied

  • Colorectal Neoplasms
  • Colonic Polyp
  • Adenoma
  • Colorectal Cancer

Keywords

  • Artificial Intelligence
  • Colonoscopy
  • Colorectal Cancer Screening
  • Adenoma Detection Rate
  • Deep Learning
03

In context

Colorectal Neoplasms

6,541 studies on the registry are indexed under Colorectal Neoplasms; 1,667 are open to participants now.

This study's planned enrollment of 3,300 is above the median of 76 across 4,800 interventional studies indexed under Colorectal Neoplasms.

Browse Colorectal Neoplasms studies →

Lead sponsor

Zhejiang University is the lead sponsor of 356 studies on the registry; 166 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
40 Years to 74 Years
Sexes eligible
All
Accepts healthy volunteers
Yes

Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.

Inclusion criteria

  1. Age 40 to 74 years, inclusive; men and women.
  2. Scheduled for elective screening, diagnostic, or surveillance colonoscopy.
  3. In generally good condition, mentally competent, and willing to provide written .

Exclusion criteria

Exclusion Criteria:

  1. Known to colonoscopy or to .
  2. History of colon cancer or previous colonic surgery.
  3. Bowel obstruction; confirmed or highly suspected colorectal cancer; inflammatory bowel disease; or active colorectal bleeding.
  4. Colorectal polyposis, including a history of familial adenomatous polyposis.
  5. Pregnancy or breastfeeding.
  6. Participation in another drug or medical device clinical trial within 1 month before enrollment.
  7. Any other condition that, in the investigator's judgment, makes the participant unsuitable for this trial.

Withdrawal Criteria:

  1. Withdrawal of consent by the participant.
  2. Inadequate bowel preparation, defined as a Boston Bowel Preparation Scale (BBPS) total score below 6 or any segment score below 2.
  3. Failure to reach the cecum.
  4. Newly diagnosed active colitis during the procedure.
Terms in these criteria, in plain language(3)

Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.

Informed consent

Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.

You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.

Contraindication

A reason a treatment, test or procedure should not be given to a particular person, such as an allergy, another illness or a medicine they take.

Biopsy and archival tissue

A biopsy takes a small piece of tissue to examine. “Archival tissue” is a sample already taken, for example at diagnosis, and kept by the hospital.

Whether a stored sample will do depends on when it was taken, how much there is and what the study needs. Ask whether the study accepts your stored sample or needs a new biopsy.

05

Study design

Phase
Not applicable
Primary purpose
Screening
Allocation
Randomized
Intervention model
Parallel assignment
Masking
Single (Participant)
Enrollment
3,300 participants (estimated)

Study arms

  • Experimental
    Experimental: AI-Assisted Colonoscopy

    Participants will undergo a high-definition colonoscopy procedure where a real-time artificial intelligence system analyzes the video feed to assist the endoscopist in identifying and highlighting suspicious lesions.

    Device: AI-Assisted Colonoscopy

  • No intervention
    Control: Conventional Colonoscopy

    Participants will undergo a standard high-definition colonoscopy procedure performed by a qualified endoscopist without the assistance of the artificial intelligence system. The AI software will not be active during these procedures.

Interventions

  • DeviceAI-Assisted Colonoscopy

    High-definition colonoscopy procedure with a real-time video analyzed artificial intelligence system.

06

What researchers measure

Primary outcomes

  1. Adenoma Detection Rate (ADR)

    The proportion of participants with at least one histologically confirmed colorectal adenoma or adenocarcinoma. Detection and specimen collection occur during the colonoscopy, with final confirmation based on pathology reports.

    Time frame: From the day of the procedure up to 14 days post-procedure.

Secondary outcomes

  1. Mean Adenomas Per Colonoscopy (APC)

    The mean number of histologically confirmed adenomas detected per participant. The number of polyps is counted during the procedure, but confirmation of adenoma status depends on pathology.

    Time frame: From the day of the procedure up to 14 days post-procedure.

  2. Advanced adenoma detection rate

    The proportion of participants with at least one histologically confirmed advanced adenoma, defined as an adenoma at least 10 mm in diameter, or with high-grade dysplasia, or with a villous component.

    Time frame: From the day of the procedure up to 14 days post-procedure.

  3. Serrated lesion detection rate

    The proportion of participants with at least one histologically confirmed flat serrated lesion, including sessile serrated lesions with or without dysplasia and traditional serrated adenomas. Hyperplastic polyps are reported separately.

    Time frame: From the day of the colonoscopy up to 14 days after the procedure.

  4. Patient Satisfaction Score

    Assessed using a 5-point Likert scale questionnaire evaluating examination comfort and acceptance of the AI system (1=very unsatisfied, 5=very satisfied).

    Time frame: Assessed within 1 hour after completion of the colonoscopy procedure.

  5. Proximal adenoma detection rate

    The proportion of participants with at least one histologically confirmed adenoma located proximal to the splenic flexure.

    Time frame: From the day of the colonoscopy up to 14 days after the procedure.

  6. Physician Satisfaction Score

    Assessed using a 5-point Likert scale questionnaire evaluating the AI system's usability and reliability (1=very unsatisfied, 5=very satisfied).

    Time frame: Assessed within 1 hour after completion of the colonoscopy procedure.

  7. Incidence of Procedure-Related Adverse Events

    The number and type of adverse events (AEs) and serious adverse events (SAEs), including but not limited to perforation, significant bleeding, and infection, are recorded.

    Time frame: From the start of the procedure up to 30 days post-procedure.

07

Study locations

1 site
08

References and documents

Individual participant data

Plan to share: No

No publications or documents are linked to this record.

09

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Sep 16, 2026, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT07307547
Responsible party
Ding Ke-Feng (Clinical professor, Zhejiang University) — Principal investigator
First posted
Dec 29, 2025
Start date
Sep 2026 (estimated)
Primary completion
Dec 2028 (estimated)
Completion
Dec 2028 (estimated)
Last update
Sep 16, 2026

Study contacts

Kefeng Ding, M.D., Ph.D.
Contact
dingkefeng@zju.edu.cn
+86-13906504783
Kefeng Ding, M.D., Ph.D.
study chair · Second Affiliated Hospital, Zhejiang University, School of Medicine

Oversight

FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

Not currently enrolling

This study is not yet recruiting, as verified in Sep 2026. You cannot join it, but the record below documents what was studied.

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